Asymptotic Normality of the Additive Regression Components for Continuous Time Processes

Simple item page
dc.creatorDebbarh, Mohammed
dc.creatorMaillot, Bertrand
dc.date2008-02-23
dc.date.accessioned2026-07-07T09:22:56Z
dc.date.available2026-07-07T09:22:56Z
dc.descriptionIn multivariate regression estimation, the rate of convergence depends on the dimension of the regressor. This fact, known as the curse of the dimensionality, motivated several works. The additive model, introduced by Stone (10), offers an efficient response to this problem. In the setting of continuous time processes, using the marginal integration method, we obtain the quadratic convergence rate and the asymptotic normality of the components of the additive model.
dc.identifierhttps://arxiv.org/abs/0802.3469
dc.identifierhttp://arxiv.org/abs/0802.3469
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/155554
dc.subjectStatistics Theory
dc.titleAsymptotic Normality of the Additive Regression Components for Continuous Time Processes
dc.typetext

Files

Collections

arXiv